Identification of prosodic phenomena is of first importance in prosodic analysis and modeling. In this paper, we introduce a new method for automatic prosodic phenomena labellin...
In this paper we propose a Neural Net-PMRS hybrid for forecasting time-series data. The neural network model uses the traditional MLP architecture and backpropagation method of tr...
- This paper presents a simulation tool targeted specifically at bang-bang type phase locked loop systems. The aim of this simulator is to quickly and accurately predict important ...
We propose a modification of the dynamic neural field model of Amari [1], aiming at reducing the simulation effort by employing spaceand frequency representations of the dynamic st...
Alexander Gepperth, Jannik Fritsch, Christian Goer...
Local pattern discovery, pattern set formation and global modeling may be viewed as three consecutive steps in a global modeling process. As each of these three steps have gained a...